Performance12 - Tanja Sanders - myThings

THE CONVERSION

MACHINE

THE NEXT BIG THING(S) IN DISPLAY

Advertising is changing…[Display ]

FROM ART…

TO SCIENCE

MAD MEN. AGE OF AGENCIES

Media Buying En Masse

Targeting Almost Non-Existent

One Creative Fits All

TO MATH MEN. AGE OF MACHINES

Programmatic Media Buying

One Creative Fits One

Real Time Advertising

Big Data

Up 7% in 2012 to total 361m eurosDutch market has grown 14.3%

Year-on-Year (IAB/Deloitte)

ONLINE DISPLAY

ONLINE AD SPEND AND DISPLAY RAPIDLY GROWING

585m512m

14.3%

310 10598255

159 170

2011H1

2012H1

170

H1

191

H1

361m336m

7%20112012

159H1

177H2

THE FUTURE OF DISPLAY

WhoIntelligent acquisition

Where New formats

WhatIntelligent personalization

How muchIntelligent media buying

?

Intelligent acquisitionWho?

Pretargeting

Dynamic display

DISPLAY DATA IS GOING UPSTREAMUPPER FUNNEL DISPLAY ADVERTISING BECOMING DATA DRIVEN

1010010011001001111

00010110100111010000111011

1100000111110101110110101000011111

000100101110001011100010110011001110110101

11111001000010010011111110101000111001011011000010

10010001010100010010010001111110110111110101010110101011100

NEW DISPLAY

10010001010100010010010001111110110111110101010110101011100

TRADITIONAL DISPLAY

LOWER FUNNEL

UPPER FUNNEL

MID FUNNEL

UPPER FUNNEL DYNAMIC DISPLAY

Optimized display campaigns over premium media

Dynamic content embedded in real time

A NEW KIND OF DISPLAY CAMPAIGN

Based on promoted product feed or best selling products

Data-less upper funnel territory a thing of the past!

PRETARGETING

Visual recognition technology

Explicit consumer intent data

New source of highly targeted, in-market traffic

NEW DISPLAY ACQUISITION, MID-FUNNEL SOLUTION

IMPLICIT VS. EXPLICIT INTENT

SEM SEARCH RETARGETING

PRETARGETING

Based on product image and meta-data

User’s intention ?

or new dress to buy???

Latest from Milan’s catwalks

User’s intention is Clear

Based on search keywords

3

HOW DOES IT WORK?

1

User browses iPod product page in shop comparison site

2Visual recognition algorithms match visited product page and advertiser’s

product feed

4User reaches product page, buys

or becomes retargeted user

Banner with matching product directs user to advertiser’s site

aa

Recognizing, in real time, at which stage user is at in conversion path and showing her optimized banner based on available data

Here’s where it all comes together

NO

NO

YES

No user intent,

advertiser site data –

best selling products

User Intent, based on

actual product

browsing

User’s interaction

with advertiser’s

website

DATA SOURCESVISITED ADVERTISER’S SITE?

Tactical

Pretargeting

Retargeting

What? Intelligent personalization

Big data

1st party data1Facebook dataf

Potential increase in retailers’ operating margins possible with big data60%

Big data. Big opportunity.

Highly valuable internal advertiser’s data that can provide a major boost to a campaign’s performance

Number of days since last

purchase

1st purcha

se total value Last

purchase

total value

Gender

Age

Amount of

purchases

Average AOV of all

purchases

Advertiser's

gross margin

per product

Channel

New/Existing users Specifi

c payment

methods

1st party data (CRM targeting)

Wake/reactivatesleeping users

Optimize for a specificsource channel

Drive repeat business from existing users

Increase AOVs

a

Hundreds of factors optimized in machine-learning algorithmic segmentation processnumber of

visits at stage X in funnel in

time frame Y

# visits to

conversion

avg./max duration of visit

avg. time

between visits

frequency of visits within time

frame

# of times

product viewed

number of

products first

visited, then

bought

maximum duration in

same product OR category

time of visit

histogram: hour,

day, week

browsing pattern – HP,

category, product, add

to cart

max # of times

specific product

visited, out of all

products not purchased

clicks

views

impressions

CTR

OS

browser geo

behavioral pattern analysis across

network

placement

domain

context/site

category

time of day

day of week

CONSUMERINTERACTION

S CAMPAIGNPERFORMANCE

USER &PUBLISHER DATA

INTENT-BASED TARGETING

OVERLAYING CONSUMER DATA OVER FB DATA

COMPANIES STILL NOT CAPITALIZING ON BIG DATA

March–April survey among digital marketers 

60%considered their organizations unprepared to handle big data

90%Failure to capitalize on big data translated to lost revenues

BIG RESULTS FOR COMPANIES WHO DO

8.18%+

1 €: 23€

300%

Average PCCR

ROI RATIO

ROI UPLIFTCOMPARED TO INITIAL FORECAST

How much? Intelligent media buying

RTB where to

Granular price control

RTB – LEADING THE DATA-DRIVEN SURGE

RTB in the US &

Worldwide

2011-2016

€ 178 million

€ 2 billion

20162011

Combined CAGR of 62%

RTB market share within display to

grow from 3% to 19%

What’s next in RTB?

Programmatic premium will likely bring more publishers on board

Video + Mobile RTB at scale

GRANULAR PRICE CONTROL

ElectricalsExcess Inventory

LEVIS JEANSiPhone 4sHigh margin product

SAMSUNG LCDsLow margin product

17% CPA

5% CPA

8% CPA

13% CPA

Advertisers can determine pricing per category and product for maximal ROI

Where? New Formats

Mobile

Video

Video PersonalizationSmart, dynamic data-driven layer

WATCH IT

Mobile Personalization

In-app retargeting App-to-app retargeting Browser-to-app retargeting

CROSS DEVICE PROFILINGThe goal:

To reach target audience on any device with personalized ads in all formats in single user purchase cycle

HTML5 First Party

Cookie

Cross-Device

App Cookie

Device Fingerprint

ing

Open UDID

UDID

EXCITING TIMES AHEAD!

Thank You

M: +31 644295411

Tanja Sanders

Tanja.sanders@mythings.com